# Сопутствующие статьи по теме Agents

Новостной центр HTX предлагает последние статьи и углубленный анализ по "Agents", охватывающие рыночные тренды, новости проектов, развитие технологий и политику регулирования в криптоиндустрии.

HashKey Accelerates AI Strategy Implementation: From Organizational Efficiency to New-Generation Digital Financial Infrastructure

HashKey Group is accelerating its AI strategy, transitioning from organizational efficiency to building next-generation digital financial infrastructure. The company has established a "Group Technology Steering Committee" to oversee the overall planning and implementation of AI and cutting-edge technologies. According to CTO Devin Zhang, the move marks a shift from fragmented, individual use of AI to a group-level systematic adoption aimed at upgrading organizational capabilities. Key priorities include improving internal operational efficiency—particularly in R&D and non-R&D functions like compliance and finance—and enhancing user experience through intent-driven interactions. Initial AI applications focus on high-repetition, measurable scenarios such as automated development pipelines, threat detection, risk management, and anti-money laundering analysis. Devin emphasized that a robust security framework is essential for financial institutions adopting AI, as agent-based systems require careful management of permissions, resource access, and accountability. HashKey is taking a compliant, risk-aware approach: prioritizing back-end and internal use cases first, while cautiously evaluating customer-facing innovations like automated trading. In the long term, HashKey envisions AI and blockchain converging, with AI agents gaining digital identities and payment capabilities, potentially making blockchain a key infrastructure for managing AI-driven economies. The company aims to boost efficiency near-term, strengthen mid-term technical foundations, and ultimately contribute to the evolution of digital financial infrastructure.

marsbit03/18 06:07

HashKey Accelerates AI Strategy Implementation: From Organizational Efficiency to New-Generation Digital Financial Infrastructure

marsbit03/18 06:07

From FOMO to Implementation: A Review of the Current State of AI Services in Crypto Companies

From FOMO to Implementation: A Look at Crypto Companies' AI Services Cryptocurrency companies, from exchanges to security firms, are rapidly integrating AI-driven services, driven by FOMO (fear of missing out) rather than just hype. Unlike previous cycles, established players like Coinbase and Binance are leading the charge, treating AI as a business necessity rather than a narrative. Key sectors adopting AI include: - **Research**: Projects like Surf AI address crypto's fragmented data problem by offering specialized tools that aggregate on-chain data, social sentiment, and metrics, providing accurate, crypto-specific insights. - **Trading**: Exchanges are leveraging AI to allow natural language commands for analysis and execution, lowering the barrier for non-developers to create automated strategies via AI agents. - **Security/Audit**: Firms like CertiK use AI to enhance smart contract audits by combining automated code scanning with human review, and adding post-audit monitoring to cover previous blind spots. - **Payment Infrastructure**: Companies are developing protocols for AI agents to make on-chain payments, using stablecoins for API fees or services, with Circle’s proposal for AI-agent payments gaining attention. The push is fueled by AI advancements like MCP and OpenClaw, which make agent-based automation accessible. However, the adoption gap between "having functionality" and "actual usage" remains, with questions about user trust in AI for real trading or payments. Ultimately, crypto firms are acting to avoid obsolescence in the AI era, though real-world utility is still evolving.

比推03/17 18:08

From FOMO to Implementation: A Review of the Current State of AI Services in Crypto Companies

比推03/17 18:08

Intelligent Computing Convergence: The Deep Integration Architecture, Paradigm Evolution, and Application Landscape of AI and Cryptocurrency Industries

The deep integration of AI and cryptocurrency represents a fundamental paradigm shift, moving beyond mere technological convergence to reshape economic and computational infrastructures. By 2025, the crypto market cap surpassed $4 trillion, signaling its maturation, while AI evolved from centralized models toward decentralized, transparent “open intelligence.” Key architectural innovations include decentralized physical infrastructure networks (DePINs) like Render and Akash, which aggregate global idle GPU resources, and platforms like Ritual that embed AI models into blockchain execution environments. Verification mechanisms such as ZKML and TEE ensure computational integrity and privacy. Bittensor introduces a token-incentivized marketplace for machine intelligence, using its Yuma consensus to reward high-performing models dynamically. AI agents have transitioned from tools to autonomous on-chain entities, capable of managing finances and executing DeFi strategies via protocols like x402 and Olas. Privacy advancements through FHE (e.g., Zama), ZKML, and TEE enable confidential on-chain computations, critical for high-stakes applications. AI also enhances security via automated smart contract auditing and real-time threat prevention systems. This fusion drives enterprise efficiency through cost reduction and secure data processing, while empowering individuals via intent-based agents and data monetization. The future points to “intelligent ledgers” where AI and blockchains are deeply architecturally coupled, enabling a fairer, decentralized digital economy.

marsbit03/17 03:13

Intelligent Computing Convergence: The Deep Integration Architecture, Paradigm Evolution, and Application Landscape of AI and Cryptocurrency Industries

marsbit03/17 03:13

From Campus to Capital: BUPT Senior Secures 30 Million Investment in 10 Days

Based on the provided text, here is the English summary: Guo Hangjiang, a 20-year-old senior student at Beijing University of Posts and Telecommunications, developed an AI engine called MiroFish in just 10 days. The project, which generates thousands of unique digital agents with distinct personalities, memories, and behaviors to simulate and predict outcomes in virtual worlds, quickly gained massive attention. It topped GitHub's global trending chart, amassing over 22,000 stars. His work caught the eye of Chinese billionaire Chen Tianqiao, former founder of Shanda Group and an advocate of the "super individual" theory. Impressed by a simple demo video, Chen committed 30 million RMB (approximately $4.1 million USD) to incubate the project, transforming Guo from an intern into a CEO overnight. MiroFish's core functionality involves processing a document (e.g., news, policy draft, novel) to extract entities and relationships into a knowledge graph using GraphRAG. It then spawns autonomous AI agents that can form groups, develop opinions, and exhibit herd mentality. A key feature is the "God's Perspective," allowing users to inject new variables (e.g., "Fed cuts rates by 50 basis points") and observe the simulated world recalibrate in real-time, enabling controlled experiments impossible in reality. The open-source framework, released under AGPL-3.0, utilizes the OASIS simulation engine, Zep Cloud for long-term memory, and is deployable via Docker. Demonstrated use cases include predicting the lost ending of the classic novel "Dream of the Red Chamber" and simulating market reactions to a Federal Reserve interest rate hike. The article notes that while MiroFish is a sophisticated multi-agent framework capable of revealing unforeseen scenarios, it has not published benchmark tests against real-world outcomes, inherits potential biases, and its simulated humans are not real. Chen Tianqio's investment is ultimately a bet on the emerging era of the "super individual."

比推03/16 06:45

From Campus to Capital: BUPT Senior Secures 30 Million Investment in 10 Days

比推03/16 06:45

AI Agents Are Starting to Register Email Accounts Themselves: This YC-Backed Company Raised $6 Million to Do Just One Thing

AI agents are now autonomously registering email accounts through AgentMail, a San Francisco-based startup that recently secured $6 million in seed funding. The company, backed by General Catalyst, Y Combinator, and prominent angels, is building email infrastructure specifically designed for AI agents—not humans. Unlike traditional email services, AgentMail provides API-first access, allowing AI agents to programmatically create accounts, send/receive emails, manage threads, and handle authentication without human intervention. This addresses a critical gap: while AI agents can perform complex tasks, they lack the identity layer (email) required to interact with most internet services. Key capabilities enabled by AgentMail include third-party authentication, bidirectional communication, automated audit trails, and multi-threaded conversations. The platform already serves thousands of human users and hundreds of thousands of AI agents, with use cases spanning supply chain coordination, customer support, loan collection, and procurement negotiations. Notably, AI agents are proactively seeking out and registering for AgentMail themselves—a sign of growing autonomy. This shift underscores a broader trend: AI agents are evolving from tools into active internet participants, necessitating new infrastructure tailored to their needs. As Box CEO Aaron Levie predicts, AI agents will soon become the primary users of software, vastly outnumbering human users in enterprises. AgentMail’s vision positions email as the foundational identity layer for this agent-centric future.

marsbit03/13 07:06

AI Agents Are Starting to Register Email Accounts Themselves: This YC-Backed Company Raised $6 Million to Do Just One Thing

marsbit03/13 07:06

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